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Meaningful Data - IxDA Helsinki 2015

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My presentation from IxDA Helsinki, hosted by Reaktor on 24 April 2015.

The title and subject matter of the presentation revolve around how data-driven growth and insight is best achieved when the data collection mechanism is understood. Google Analytics, for example, is not a very useful tool if just installed and never configured. This "Plug-and-play Analytics" is one of the reasons many get frustrated with the platform.

There are many ways to make the platform work for your KPIs and KBOs (Key Business Objectives), but it does require that you know how the platform works, and how you can tweak the data collection mechanism to maximize data quality for your hypotheses.

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Meaningful Data - IxDA Helsinki 2015

  1. 1. Meaningful Data @SimoAhava #IxDAHel
  2. 2. Simo Ahava Google Developer Expert Senior Data Advocate, Reaktor www.simoahava.com Twitter: @SimoAhava Google+: +SimoAhava @SimoAhava #IxDAHel
  3. 3. Agenda 1. The Schema Conspiracy 2. The hunt for Meaningful Data 3. Survival tips @SimoAhava #IxDAHel
  4. 4. The Schema Conspiracy @SimoAhava #IxDAHel
  5. 5. Google Analytics is a tool designed to work for 9,163,750* businesses @SimoAhava #IxDAHel * Author’s estimate, not an official figure
  6. 6. It is thus conceivable Google doesn’t know what your business KPIs are @SimoAhava #IxDAHel
  7. 7. And yet we still rarely go beyond the default @SimoAhava #IxDAHel
  8. 8. DEAR BOSS, Last month, the number of Sessions on our site was… 2,578,000 ...which is an uplift of +2.78% compared to last month. @SimoAhava #IxDAHel
  9. 9. DEAR BOSS, Last month, the eCommerce Conversion Rate on our site was… 21.20% ...which is an uplift of +5% compared to last month. @SimoAhava #IxDAHel
  10. 10. All metrics and dimensions used by a data collection / processing / reporting platform subscribe to the schemas of said platform.
  11. 11. All metrics and dimensions used by a data collection / processing / reporting platform subscribe to the schemas of said platform. Sessionization Schema
  12. 12. All metrics and dimensions used by a data collection / processing / reporting platform subscribe to the schemas of said platform. Event Tracking Schema
  13. 13. All metrics and dimensions used by a data collection / processing / reporting platform subscribe to the schemas of said platform. Transactional Schema
  14. 14. This has two major implications on how we should approach data @SimoAhava #IxDAHel
  15. 15. 1 @SimoAhava #IxDAHel All sessionized data is arbitrary
  16. 16. @SimoAhava #IxDAHel
  17. 17. @SimoAhava #IxDAHel Fictional
  18. 18. @SimoAhava #IxDAHel Fictional Fictional
  19. 19. @SimoAhava #IxDAHel Fictional Fictional Fictional
  20. 20. @SimoAhava #IxDAHel Fictional Fictional Fictional Fictional
  21. 21. How can an arbitrary, fictional metric ever be a good KPI?* @SimoAhava #IxDAHel * Rhetorical question, it can’t
  22. 22. 2 @SimoAhava #IxDAHel Data quality is achieved, not acquired
  23. 23. Stay away from aggregate metrics. @SimoAhava #IxDAHel
  24. 24. Stay away from aggregate metrics. Segment, customize, combine, visualize. @SimoAhava #IxDAHel
  25. 25. Aggregate Segmented User-centric Integrated Predictive @SimoAhava #IxDAHel Our website’s eCommerce Conversion Rate for January was... 21.20%
  26. 26. Aggregate Segmented User-centric Integrated Predictive @SimoAhava #IxDAHel Visitors who landed on our website through our January Facebook campaign had an eCommerce Conversion Rate of.... 12.57%
  27. 27. Aggregate Segmented User-centric Integrated Predictive @SimoAhava #IxDAHel Visitors with no previous transactions, who landed on our site through the January Facebook campaign, converted at a rate of... 28.12%
  28. 28. Aggregate Segmented User-centric Integrated Predictive @SimoAhava #IxDAHel Our customers from Espoo between the ages 17–24, who landed on our site through the January Facebook campaign, converted at a rate of... 13.50%
  29. 29. Aggregate Segmented User-centric Integrated Predictive @SimoAhava #IxDAHel Based on our customer segments, on our campaign efficiency across channels, on seasonality, and on current competition, we predict that the following constraints apply to our Spring campaigns:
  30. 30. The hunt for Meaningful Data @SimoAhava #IxDAHel
  31. 31. Idea #1: Enrich data Q: How can I correlate weather with online bookings on a golf course? @SimoAhava #IxDAHel
  32. 32. Idea #1: Enrich data Today @SimoAhava #IxDAHel
  33. 33. Idea #1: Enrich data Today @SimoAhava #IxDAHel
  34. 34. Idea #1: Enrich data 1. Visitor lands on website 2. Geolocate visitor using their IP address 3. Query for weather conditions using OpenWeatherMap API 4. Annotate session with weather data 5. Segment sessions by weather condition and verify correlation @SimoAhava #IxDAHel
  35. 35. Idea #1: Enrich data Weather - type Path Length Revenue Average Order Value Per Session Value Clear 0 €7,887.60 €55.00 €3.15 Clouds 0 €3,454.20 €70.00 €2.03 Rain 0 €565.00 €75.00 €0.12 http://goo.gl/NwyBaj @SimoAhava #IxDAHel
  36. 36. Idea #1: Enrich data NEXT STEPS - Query for “next weekend” or “upcoming holiday” forecast instead - Automatic bid adjustment due to weather conditions - Push campaigns for golf simulator, club house benefits, sauna, etc. if weather is horrible @SimoAhava #IxDAHel
  37. 37. Idea #2: Enrich and integrate data Q: How do I get full customer journey from first exposure to booking to shopping on the boat? @SimoAhava #IxDAHel
  38. 38. Idea #2: Enrich and integrate data Average order value from online channels: 750€ 250€ Revenue per customer: Customer Shopping Eating Fun A3224 12€ 20€ 20€ A3225 175€ 100€ 120€ @SimoAhava #IxDAHel
  39. 39. Idea #2: Enrich and integrate data Average order value from online channels: 750€ 250€ Revenue per customer: Customer Shopping Eating Fun A3224 12€ 20€ 20€ A3225 175€ 100€ 120€ @SimoAhava #IxDAHel
  40. 40. Idea #2: Enrich and integrate data 1. Visitor lands on website 2. Their session is annotated with their unique ClientID 3. This ClientID is also sent with the booking to the CRM 4. On board, the key card registers all purchases to this ClientID 5. Finally, data is pulled out of the web analytics platform and the CRM, and combined in Tableau @SimoAhava #IxDAHel
  41. 41. Idea #2: Enrich and integrate data True average order value from online channels: 850€ 1250€ @SimoAhava #IxDAHel
  42. 42. Survival tips @SimoAhava #IxDAHel
  43. 43. Tip #1: Explore beyond defaults @SimoAhava #IxDAHel Be critical: Plug-and-play analytics is not conducive to data-driven insight.
  44. 44. Tip #2: Be aware of the Schema @SimoAhava #IxDAHel Be critical: Focusing on heavily sessionized metrics might not be relevant.
  45. 45. Tip #3: The 3 rules of data collection @SimoAhava #IxDAHel 1. Rule of data passivity :: data does nothing, data beats nothing. It’s a passive medium and requires an active agent (analyst) to interpret. 2. Rule of data subjectivity :: any interpretation of data relies on a well-formulated hypothesis. Whether data is ”bad” or ”good” depends on what you want to know. 3. Rule of data scarcity :: no matter what you do, you will never have all the data. An arbitrary line must be drawn, and you must understand where and why this artificial limit exists.
  46. 46. Tip #4: BE CRITICAL @SimoAhava #IxDAHel Data quality is directly proportional to your understanding of the data collection method.
  47. 47. Bonus tip @SimoAhava #IxDAHel read www.simoahava.com
  48. 48. Thank you! simoahava.com reaktor.com Twitter: @SimoAhava Google+: +SimoAhava Email: simo.ahava@reaktor.fi @SimoAhava #IxDAHel

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